Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Applications of IR Spectroscopy: Overview01:11

Applications of IR Spectroscopy: Overview

878
The non-destructive nature and ability to provide valuable chemical information make IR spectroscopy a versatile technique with broad applications in various scientific and industrial fields. IR spectroscopy is commonly used to identify and characterize organic and inorganic compounds. It provides information about the functional groups present in a molecule and the bonding between atoms. This helps in the structural elucidation of compounds during organic synthesis, pharmaceutical research,...
878
Sample Preparation for Analysis: Advanced Techniques01:08

Sample Preparation for Analysis: Advanced Techniques

414
Accurate analysis of complex samples often requires advanced preparation techniques to achieve reliable and reproducible results. Samples containing inorganic or organic materials can be challenging to dissolve or decompose effectively. Standard sample preparation methods include acid digestion, fusion, dry ashing, and wet digestion.
Acid digestion with strong acids is commonly used to dissolve inorganic materials that are insoluble (do not dissolve) in water. This method can be useful for...
414
Sample Preparation for Analysis: Overview01:21

Sample Preparation for Analysis: Overview

287
Sample preparation is an essential step in the analytical process. It involves preparing a sample so that it can be analyzed accurately. The goal is to extract the analyte, the substance you want to measure, from the sample while removing any components that may interfere with the analysis. Sample preparation techniques vary depending on the physical state of the sample.
Bulk or large solid samples are typically reduced in size using grinding, crushing, or milling techniques to increase the...
287
Ultraviolet and Visible (UV–Vis) Spectroscopy: Overview01:02

Ultraviolet and Visible (UV–Vis) Spectroscopy: Overview

2.9K
Ultraviolet–visible (UV–visible or UV–Vis) spectroscopy is an analytical technique that investigates the interaction between matter and UV–Vis light within the electromagnetic spectrum. This method is widely used for its versatility, simplicity, and relatively quick data acquisition, making it valuable for both qualitative and quantitative analysis. When UV–Vis radiation passes through a material,  molecules absorb light depending on the energy required for...
2.9K
IR Spectrometers01:25

IR Spectrometers

1.2K
There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
1.2K
Sampling Methods: Overview01:06

Sampling Methods: Overview

405
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
405

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Retraction Note: Comprehensive in vivo and in silico approaches to explore the hepatoprotective activity of poncirin against paracetamol toxicity.

Naunyn-Schmiedeberg's archives of pharmacology·2026
Same author

Retraction notice to "Corrigendum to "Suppression of TRPV1 and P2Y nociceptors by honokiol isolated from Magnolia officinalis in 3rd degree burn mice by inhibiting inflammatory mediators" [Biomed. Pharmacother. 114 (2019) 108777]" [Biomedicine & Pharmacotherapy 186 (2025) 117988].

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie·2026
Same author

Retraction notice to "Suppression of TRPV1 and P2Y nociceptors by honokiol isolated from Magnolia officinalis in 3<sup>rd</sup> degree burn mice by inhibiting inflammatory mediators" [Biomedicine & Pharmacotherapy 114 (2019) 108777].

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie·2026
Same author

Retraction notice to "Pharmacological mechanism of xanthoangelol underlying Nrf-2/TRPV1 and anti-apoptotic pathway against scopolamine-induced amnesia in mice" [Biomedicine & Pharmacotherapy 150 (2022) 113073].

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie·2026
Same author

How leader-enforced positivity and humility-aspiration signaling shape emotional exhaustion and unethical behavior: evidence for distinct psychological pathways.

Frontiers in psychology·2026
Same author

Trends in sugar-sweetened beverage prices, sales, and elasticities: policy evidence from WHO regions, 2010-2024.

Frontiers in public health·2026

Related Experiment Video

Updated: Aug 14, 2025

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
06:50

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

Published on: November 8, 2019

6.7K

Machine Learning-Enabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly

Hussain Ali1, Prakash Muthudoss2, Manikandan Ramalingam3

  • 1Christ (Deemed to Be University), Bangalore, 560029, Karnataka, India.

AAPS Pharmscitech
|January 10, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a method for selecting high-quality pharmaceutical data subsamples using quality metrics and visualization. It demonstrates successful model transferability from lab to production scales for artificial neural network-multilayer perceptron (ANN-MLP) models.

Keywords:
NIR spectroscopyartificial neural network-multilayer perceptron (ANN-MLP)data qualitymachine learning

More Related Videos

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

10.7K
Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.5K

Related Experiment Videos

Last Updated: Aug 14, 2025

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
06:50

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression

Published on: November 8, 2019

6.7K
Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

10.7K
Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.5K

Area of Science:

  • Pharmaceutical data science and machine learning applications.
  • Spectroscopic data analysis and chemometrics.
  • Quality control and process analytical technology (PAT) in drug manufacturing.

Background:

  • Large pharmaceutical datasets pose challenges for machine learning model development.
  • High-quality, representative data is crucial for reliable machine learning models.
  • Previous work established a workflow for near-infrared (NIR) spectroscopy data acquisition.

Approach:

  • Developed a systematic method for selecting representative subsamples from historical pharmaceutical research data.
  • Implemented a comprehensive suite of quality measures, diagnostic tools, and visualization strategies.
  • Utilized an open-source tablet dataset with variations in dosage, shape, size, manufacturing scale, and coating.

Key Points:

  • Demonstrated the impact of hyperparameter selection on artificial neural network-multilayer perceptron (ANN-MLP) model performance.
  • Discussed hyperparameter tuning approaches and their performance relative to existing references.
  • Successfully extended machine learning models from lab-scale to pilot-scale and production-scale data.

Conclusions:

  • The presented quality metrics and visualization strategy effectively aid in subsample selection from existing studies.
  • The workflow is validated using real-world near-infrared (NIR) data, showcasing its practical applicability.
  • Model transferability across different manufacturing scales is achievable, enhancing the robustness of pharmaceutical machine learning applications.